rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Nonparametric and parametric estimation of wave statistics and spectra
  name:
    name part: Yamazaki, Hidekatsu
    name part: 1955-
    role:
      role term: creator
  name:
    name part: Herbich, John B.
    role:
      role term: degree supervisor.
  name:
    name part: Newton, H. Joseph
    role:
      role term: degree committee member.
  name:
    name part: Reid, Robert Osborne
    role:
      role term: degree supervisor.
  name:
    name part: Schumaker, Larry L.
    role:
      role term: degree committee member.
  name:
    name part: Venezian, Giulio
    role:
      role term: degree committee member.
  name:
    name part: Texas A & M University
    role:
      role term: degree granting institution.
  type of resource: text
  genre: bibliography
  genre: Academic theses
  origin info:
    place:
      place term: xx
    date issued: 1984
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: print
    extent: xii, 160 leaves : illustrations ; 29 cm
  abstract: A nonparametric bivariate density estimation technique is developed employing tensor product B-splines to provide a concise wave data summary. Most of the existing nonparametric techniques involve a certain level of subjectivity in the choice of smoothing parameters. A criterion based on the least squares concept is proposed to remove the subjective choice of smoothing parameters. Numerical experiments, in which random variables are generated from a known bivariate independent normal distribution and the modified Longuet-Higgins distribution, show that the technique reproduces the population density functions well. However, due to lack of the shape preserving property of B-splines, the positivity of the density function cannot be guaranteed. An alternative spectral estimation procedure is proposed, extending the idea of Bretschneider (1959). The alternative spectrum is the second moment of the wave height of the joint probability density function (pdf) in terms of the frequency domain, and is named the PDF spectra. Comparison of the latter with other spectral estimators such as the FFT spectral window estimator and the autoregressive spectral estimator shows good agreement. The nonparametric joint pdf provides a concise representation of long-term wave data from which one can obtain not only the usual wave statistics, but the wave spectra as well. That is, the wave spectrum is simply a subset statistical function contained in the bivariate pdf for wave height and period.
  note: "Major subject: Ocean Engineering."
  note: Typescript (photocopy).
  note: Vita.
  note: Ph. D. Texas A & M University 1984
  note: Includes bibliographical references (leaves 154-159).
  subject:
    topic: Spectrum analysis
  subject:
    topic: Wave mechanics
  subject:
    topic: Major ocean engineering
  identifier: http://proxy.library.tamu.edu/login
  identifier: https://hdl.handle.net/1969.1/DISSERTATIONS-588781
  identifier: http://gateway.proquest.com/openurl
  related item:
    location:
      url: http://proxy.library.tamu.edu/login
  related item:
    location:
      url: https://hdl.handle.net/1969.1/DISSERTATIONS-588781
  related item:
    location:
      url: http://gateway.proquest.com/openurl
  record info:
    record content source: TXA
    record creation date: 850912
    record change date: 20220103135443.0
    record identifier: in00000563522
    language of cataloging:
      language term: eng